CN101222348A - Method and system for calculating number of website real user - Google Patents
Method and system for calculating number of website real user Download PDFInfo
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- CN101222348A CN101222348A CNA2007100000853A CN200710000085A CN101222348A CN 101222348 A CN101222348 A CN 101222348A CN A2007100000853 A CNA2007100000853 A CN A2007100000853A CN 200710000085 A CN200710000085 A CN 200710000085A CN 101222348 A CN101222348 A CN 101222348A
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Abstract
The present invention discloses a method for counting real users of a website, comprising the following steps that: a website server detects user recognition information and a Cookie ID sent by a user; the website server compares the user recognition information and the Cookie ID with the user recognition information and the Cookie ID existed in an entity user set; the website server manages the relative information of the user according to the comparison result. The invention further provides a system for counting real users of a website. The invention solves the problem of managing users who apply a plurality of account numbers; the website server makes the virtual users in network correspond to the real users in real life to collect all of the user information of a real user registered on the website server and to collect the behavior information of the user who accesses the website server with an unregistered identity, rather than limitedly analyzing the information, behavior and property of single virtual user.
Description
Technical field
The present invention relates to network user's registered information managing technical field, relate in particular to a kind of method and system of calculating number of website real user.
Background technology
During user's Website login, need information such as input username and password, the website by this user of above-mentioned information Recognition after, could provide corresponding service to this user.The username and password of user's input normally oneself is set, and has very big randomness, and promptly a real user can be provided with a plurality of different username and passwords.A plurality of username informations of storing in the website may all belong to same real user, yet which user name this website can't distinguish is for which real user, can only regard these user names as belong to different real user respectively.
Exist a real user to register a plurality of numbers of the account (as user ID) on the website, movable on the website with different numbers of the account then, the website can only be independent the behavior that traces into unique user ID, can only grasp user's behavior and information from the part, collect the partial data of an entity user, can not understand real behavior of user and information on the whole.
Therefore, need carry out association to all user names of a real user in some field, carry out unified management, for example, the ID card No. in banking in the log-on message of use real user is as association, be that the account that same ID card No. is opened is the account of same entity user, after all records of this account all are recorded, do as a whole the application, such as the credit grade of judging this user, search this user's poor record, judge this user's loan repayment capacity etc.
Yet, the website can utilize unique proof of identification information association to the paying customer, for example when Website login, require the user that proof of identification is provided, the information that real user such as corporate licence are unique, but a large amount of free members and unregistered user are arranged on the website, requiring them to provide such obvious threshold of information too high, be difficult to accept concerning the user, also is very high concerning the operation cost of website.
Another kind of mode is to utilize information that client collects the user as association, collects same the user profile on the computer with the mode of hardware or software, by unique sign as association, thereby judge unique entity user.For example, the U shield of banking system, it is the digital certificate that industrial and commercial bank is used for discerning client identity in a kind of network environment, a kind of hardware in kind that is similar to flash memory with intelligent chip and shape, the client who has the U shield except needs are submitted Web bank's username and password to, also needs the U shield is inserted USB interface of computer when using Web bank, after bank's process multiple-authentication is errorless, the account that just allows to enter internet banking operation oneself; The dongle of financial system and for example, developer's program is operated dongle by the interface module of calling the dongle development kit and providing, and dongle responds this operation and by interface module corresponding data is returned to developer's program; The machine code of perhaps collecting subscriber computer is as sign.
But above method all needs the client to pay certain cost, is infeasible basically concerning vast free member and non-registered users; And because whether the user can select to install, if client is not installed, data just have no idea to collect, if force to install, collect user's information by force or in the dark, also do not allow legally.
Summary of the invention
The problem to be solved in the present invention provides a kind of method and system of calculating number of website real user, can not be in the prior art to solve with a plurality of user ID of a real user registration, and this real user non-registered users of behavior on the website is associated, thereby really judges the behavior of a real user and the defective of information on the whole.
In order to realize above purpose, the invention provides a kind of method of calculating number of website real user, may further comprise the steps:
Website server detects customer identification information and the Cookie ID that the user sends;
Described Website server compares described customer identification information and Cookie ID customer identification information and the Cookie ID concentrated with being present in entity user;
Described Website server manages described user related information according to comparative result.
Preferably, described described user related information being managed specifically according to comparative result comprises:
If described customer identification information belongs to the entity user that entity user is concentrated, and does not have described Cookie ID in the described entity user, then described Website server adds described entity user with described Cookie ID;
If described Cookie ID belongs to the entity user that described entity user is concentrated, and does not have described customer identification information in the described entity user, then described Website server adds described entity user with described customer identification information;
If described customer identification information and described Cookie ID do not belong to the entity user that described entity user is concentrated, then described Website server joins the novel entities user that described entity user is concentrated with described customer identification information and described Cookie ID;
If described customer identification information and described Cookie ID belong to described entity user collection, judge then whether described customer identification information and described Cookie ID belong to same entity user, if do not belong to same entity user, then merge into an entity user.
Preferably, before detecting, the website also comprises:
The user sends log messages by subscriber equipment to described Website server;
Described Website server judges whether comprise Cookie ID in the described log messages, if do not have, then is that described subscriber equipment is created a Cookie ID, records in the entity user of entity user collection, and notifies described subscriber equipment.
Preferably, described Website server is also to comprise behind the described user equipment allocation Cookie ID: subscriber equipment is deleted described Cookie ID.
Preferably, described customer identification information comprises user ID.
The present invention also provides a kind of system of calculating number of website real user, comprises Website server and subscriber equipment, and described Website server further comprises detecting unit, comparing unit and administrative unit;
Described detecting unit is used to detect customer identification information and the Cookie ID that the user sends by subscriber equipment;
Described comparing unit is connected with described detecting unit, is used for described customer identification information and CookieID and has been present in customer identification information and the Cookie ID that the entity user of Website server concentrates comparing;
Described administrative unit is connected with described comparing unit, is used for according to described comparative result described user related information being managed.
Preferably, described administrative unit manages specifically described user related information according to described comparative result and comprises:
If described customer identification information belongs to the entity user that entity user is concentrated, and does not have described Cookie ID in the described entity user, then described Website server adds described entity user with described Cookie ID;
If described Cookie ID belongs to the entity user that described entity user is concentrated, and does not have described customer identification information in the described entity user, then described Website server adds described entity user with described customer identification information;
If described customer identification information and described Cookie ID do not belong to the entity user that described entity user is concentrated, then described Website server joins the novel entities user that described entity user is concentrated with described customer identification information and described Cookie ID;
If described customer identification information and described Cookie ID belong to described entity user collection, judge then whether described customer identification information and described Cookie ID belong to same entity user, if do not belong to same entity user, then merge into an entity user.
Preferably, also comprise memory cell, be connected, be used to store the entity user collection of subscriber equipment with described comparing unit.
Preferably, described entity user collection comprises that customer identification information and Website server are the Cookie ID of user equipment allocation.
Preferably, also comprise Cookie ID allocation units, be used to the user equipment allocation Cookie ID of login for the first time, and described Cookie ID is stored in described memory cell.
Preferably, described customer identification information comprises user ID.
Compared with prior art, the present invention has the following advantages:
The invention solves the problem that Website server manages for the real user of applying for a plurality of numbers of the account, information, behavior and the attribute of the single Virtual User of analysis that Website server is no longer unilateral, but with Virtual User on the network and the real user correspondence in the reality, collect all user profile that a real user is registered on Website server, for example user name, user cipher etc.; And with the behavioural information of non-registered users identity on Website server, for example subscriber mailbox address, telephone number etc.; Thereby can be used multianalysis.
In addition, the present invention utilizes Cookie ID and user ID as related, and application cost is very low, and the user is not had the cost that any needs are paid, and the not influence of application to the user does not have jural risk yet.
Description of drawings
Fig. 1 is the system construction drawing of a kind of calculating number of website real user of the present invention;
Fig. 2 is the method flow diagram of a kind of calculating number of website real user of the present invention;
Fig. 3 is the specific embodiment flow chart of Fig. 2.
Embodiment
Core concept of the present invention is: the user of Website login server on same computer, corresponding same Cookie ID.For unregistered be the user of website members, Website server only writes down its CookieID; For the user who is registered as website members, Website server writes down its user ID and Cookie ID.Website server is according to the corresponding relation of user ID and Cookie ID, the Cookie ID that judges same user ID correspondence belongs to an entity user, the user ID of same Cookie ID correspondence belongs to same entity user, this belongs to same entity user to user ID and Cookie ID simultaneously, thereby system specifies corresponding some entity user (User) with one group of user ID and Cookie ID, and gives a numbering (User ID).Website server can be according to the information multianalysis single virtual user's of an entity user information, behavior and attribute.
The present invention introduces enterprise customer and two notions of personal user, and generally speaking, the user who uses international website to carry out commercial activity is enterprise customer, for example big, medium-sized and small enterprises or purchaser etc. mostly.Because commercial activity is carried out in the Internet bar just as use Web bank in the Internet bar, there is stolen risk in user profile, safety is difficult to guarantee, therefore the enterprise customer uses the computer of enterprises usually, use the likelihood ratio of public place computer less, a plurality of users use the probability of computer on the same stage just littler simultaneously.And the present invention mainly is statistics enterprise customer's a information, does not get rid of the situation of wrong association certainly, if the personal user can provide enterprise customer's legal testimonial material when login, the website also can be as treating enterprise customer's statistical correlation user profile.
According to the statistics of certain large-scale Chinese website, had only 10% Chinese website member (enterprise customer and the user of nonbusiness) to utilize Internet bar's online in 2002, this ratio today after 4 years should drop to lower; Wherein, the enterprise customer uses the ratio of the computer log Chinese website of public places such as Internet bar can ignore especially.In addition, for foreign language website, owing to relate to the foreign trade commercial affairs mostly, its threshold that enters is higher than Chinese website, and therefore, the enterprise customer utilizes the probability of personal computer logins such as Internet bar lower.Therefore, above-mentioned data can illustrate that different enterprise customers uses the probability of same computer very low, and use the probability of the own computer of enterprise very high.In addition, even there is different enterprise customers to use the situation of same computer to take place, they visit the probability of same website also can be very low.
Therefore, the present invention can think a real user in the corresponding reality of same user ID, no matter this user ID is logined on which platform computer, thinks that all this is the behavior of same real user; And think that it is the behavior of a real user or same company that the user who uses same computer log Website server has very high probability.
The invention provides a kind of calculating number of website real user system, as shown in Figure 1, comprise Website server 100 and a plurality of subscriber equipment 200, Website server 100 further comprises detecting unit 101, comparing unit 102, administrative unit 103, memory cell 104 and Cookie ID allocation units 105.
Wherein, detecting unit 101 is used to detect customer identification information and the Cookie ID that the user sends by subscriber equipment 200; Comparing unit 102 is connected with detecting unit 101, is used for customer identification information and Cookie ID that customer identification information and Cookie ID and the entity user that has been present in Website server 100 are concentrated are compared; Administrative unit 103 is connected with comparing unit 102, is used for according to comparative result user related information being managed; Memory cell 104 is connected with comparing unit 102, is used for storage entity user collection, and entity user is concentrated may comprise a plurality of entity user, and each entity user comprises that customer identification information and Website server are the Cookie ID of user equipment allocation; Cookie ID allocation units 105 are used to the user equipment allocation Cookie ID of login for the first time, and Cookie ID is stored in memory cell 104.
Website server can be added up the information of the real user of logining this website according to the information of above-mentioned entity user, and, realize unified management is carried out in the behavior of real user according to the information multianalysis single virtual user's of a real user information, behavior and attribute.
The present invention also provides a kind of method of calculating number of website real user, as shown in Figure 2, may further comprise the steps:
Step s201, Website server detects customer identification information and the Cookie ID that the user sends by subscriber equipment.Wherein, customer identification information comprises information such as user ID, user cipher, addresses of items of mail for registered user, for unregistered user, does not comprise user ID; Subscriber equipment is generally the computer that the user uses; Cookie is some small text files that Website server is created on the computer that the user uses, these files are used to store the site access information of collecting relevant user, website comprising visit, operation of carrying out and any personal information that provides, Website server uses the information among the Cookie that personalized content is provided, finish transaction and collect statistics, as long as the user has browsed the website, just can login according to the user, actions such as registration stay corresponding Cookie, as long as the user does not remove this Cookie, when then next user visits once more, the website just can be known user's partial information, for example Email address according to the information of preserving among this Cookie, user name etc.
Step s202, Website server compares customer identification information and Cookie ID customer identification information and the Cookie ID concentrated with being present in entity user.
Step s203, Website server manages user related information according to comparative result, if customer identification information belongs to the entity user that entity user is concentrated, and does not have Cookie ID in the entity user, then Website server adds entity user with Cookie ID; If Cookie ID belongs to the entity user that entity user is concentrated, and does not have customer identification information in the entity user, this customer identification information is that the probability of same entity user is very high, and then Website server adds entity user with customer identification information; If customer identification information and Cookie ID do not belong to the entity user that entity user is concentrated, then Website server joins the novel entities user that entity user is concentrated with customer identification information and Cookie ID; If customer identification information and Cookie ID belong to the entity user collection, judge then whether customer identification information and Cookie ID belong to same entity user, if do not belong to same entity user, then merge into an entity user.
Subscriber equipment for logining on Website server for the first time also comprised before step s201:
Website server generates unique, a unduplicated Cookie ID (being that the IP address adds sequence number): the user sends log messages by subscriber equipment to Website server, Website server judges whether comprise Cookie ID in the log messages, if do not have, then create a Cookie ID for subscriber equipment, record in the entity user of entity user collection, and notifying user equipment.Can preserve this Cookie ID in the computer of user's login, this Cookie ID is effectively permanent, unless the user deletes voluntarily, otherwise when user's Website login server, Website server can be judged, if the CookieID that is deposited in the computer at this user place is Website server Already in, then this computer had been logined this Website server, and this Website server is the new Cookie of regeneration not.
In conjunction with the basic principle flow chart of the present invention of Fig. 2, concrete Application Example of the present invention as shown in Figure 3, Website server is collected user ID and Cookie id information; Website server is included into the entity user collection with user ID and CookieID information; Website server judges whether new user ID and the Cookie id information that receives has been present in the entity user collection, if customer identification information belongs to the entity user that entity user is concentrated, and do not have Cookie ID in the entity user, then Website server adds entity user with Cookie ID; If Cookie ID belongs to the entity user that entity user is concentrated, and does not have customer identification information in the entity user, then Website server adds entity user with customer identification information; If customer identification information and CookieID do not belong to the entity user that entity user is concentrated, then Website server joins the novel entities user that entity user is concentrated with customer identification information and Cookie ID; If customer identification information and Cookie ID belong to the entity user collection, judge then whether customer identification information and Cookie ID belong to same entity user, if do not belong to same entity user, then merge into an entity user.
Following example is the concrete application of the present invention in several actual scenes:
Real user is the Website login server for the first time, and is movable on the website with the identity of non-registered users earlier, then is registered as the member.When real user during with the identity Website login server of non-registered users, Website server can be provided with a Cookie on its computer, and simultaneity factor is noted this Cookie ID, and corresponds to an entity user; Then this real user is registered the member, and Website server is noted its user ID, and according to same Cookie ID, this user ID is also corresponded to same entity user.
Because when user ID difference and Cookie ID are identical, this user ID is that the probability of same real user is very high, therefore, same real user is on same computer, with a plurality of user ID Website login servers, Website server is noted these user ID, and according to same Cookie ID, these user ID is also corresponded to same entity user.If Website server is judged these user ID and once logined this Website server on other computers, the original corresponding entity user of these user ID and the entity user of the Cookie ID correspondence on this computer can be merged into an entity user.
Real user is used identical user ID Website login on the various computing machine.Website server judges whether this computer once logined the website, if do not login, Website server can be provided with a Cookie on its computer, simultaneity factor is noted this Cookie ID, and, this Cookie ID is corresponded to same entity user according to same user ID; If logined, entity user and the original corresponding entity user of this login user ID that Website server can be corresponding originally with the Cookie ID on this computer are merged into an entity user.
Real user is Cookie deletion back Website login, and movable on the website if real user with the non-registered users activity, is perhaps registered after the new user ID, Website server corresponds to a novel entities user with this Cookie ID or new user ID; If the account number of login is the account number of logining originally, entity user is logined with original user ID, and the Cookie ID that Website server can be new with this corresponds to the entity user of this user ID correspondence.
More than disclosed only be several specific embodiment of the present invention, still, the present invention is not limited thereto, any those skilled in the art can think variation all should fall into protection scope of the present invention.
Claims (11)
1. the method for a calculating number of website real user is characterized in that, may further comprise the steps:
Website server detects customer identification information and the Cookie ID that the user sends;
Described Website server compares described customer identification information and Cookie ID customer identification information and the Cookie ID concentrated with being present in entity user;
Described Website server manages described user related information according to comparative result.
2. the method for calculating number of website real user according to claim 1 is characterized in that described described user related information being managed specifically according to comparative result comprises:
If described customer identification information belongs to the entity user that entity user is concentrated, and does not have described Cookie ID in the described entity user, then described Website server adds described entity user with described Cookie ID;
If described Cookie ID belongs to the entity user that described entity user is concentrated, and does not have described customer identification information in the described entity user, then described Website server adds described entity user with described customer identification information;
If described customer identification information and described Cookie ID do not belong to the entity user that described entity user is concentrated, then described Website server joins the novel entities user that described entity user is concentrated with described customer identification information and described Cookie ID;
If described customer identification information and described Cookie ID belong to described entity user collection, judge then whether described customer identification information and described Cookie ID belong to same entity user, if do not belong to same entity user, then merge into an entity user.
3. the method for calculating number of website real user according to claim 1 is characterized in that, also comprises before Website server detects:
The user sends log messages by subscriber equipment to described Website server;
Described Website server judges whether comprise Cookie ID in the described log messages, if do not have, then is that described subscriber equipment is created a Cookie ID, records in the entity user of entity user collection, and notifies described subscriber equipment.
4. as the method for calculating number of website real user as described in the claim 3, it is characterized in that described Website server is also to comprise behind the described user equipment allocation Cookie ID: described subscriber equipment is deleted described Cookie ID.
5. as the method for calculating number of website real user as described in each in the claim 1 to 4, it is characterized in that described customer identification information comprises user ID.
6. the system of a calculating number of website real user comprises Website server and subscriber equipment, it is characterized in that, described Website server further comprises detecting unit, comparing unit and administrative unit;
Described detecting unit is used to detect customer identification information and the Cookie ID that the user sends by subscriber equipment;
Described comparing unit is connected with described detecting unit, is used for described customer identification information and CookieID and has been present in customer identification information and the Cookie ID that the entity user of Website server concentrates comparing;
Described administrative unit is connected with described comparing unit, is used for according to described comparative result described user related information being managed.
7. as the system of calculating number of website real user as described in the claim 6, it is characterized in that described administrative unit manages specifically described user related information according to described comparative result and comprises:
If described customer identification information belongs to the entity user that entity user is concentrated, and does not have described Cookie ID in the described entity user, then described Website server adds described entity user with described Cookie ID;
If described Cookie ID belongs to the entity user that described entity user is concentrated, and does not have described customer identification information in the described entity user, then described Website server adds described entity user with described customer identification information;
If described customer identification information and described Cookie ID do not belong to the entity user that described entity user is concentrated, then described Website server joins the novel entities user that described entity user is concentrated with described customer identification information and described Cookie ID;
If described customer identification information and described Cookie ID belong to described entity user collection, judge then whether described customer identification information and described Cookie ID belong to same entity user, if do not belong to same entity user, then merge into an entity user.
8. as the system of calculating number of website real user as described in the claim 6, it is characterized in that, also comprise memory cell, be connected, be used to store the entity user collection of subscriber equipment with described comparing unit.
9. as the system of calculating number of website real user as described in the claim 8, it is characterized in that described entity user collection comprises that customer identification information and Website server are the Cookie ID of user equipment allocation.
10. as the system of calculating number of website real user as described in the claim 6, it is characterized in that, also comprise Cookie ID allocation units, be used to the user equipment allocation Cookie ID of login for the first time, and described Cookie ID is stored in described memory cell.
11., it is characterized in that described customer identification information comprises user ID as the system of calculating number of website real user as described in each in the claim 6 to 10.
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Cited By (49)
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---|---|---|---|---|
CN102063505A (en) * | 2011-01-06 | 2011-05-18 | 百度在线网络技术(北京)有限公司 | Information promoting method and system |
CN102073695A (en) * | 2010-12-28 | 2011-05-25 | 汉柏科技有限公司 | Progressive statistical method |
CN102426580A (en) * | 2010-09-17 | 2012-04-25 | 微软公司 | Detecting potential fraudulent online user activity |
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US9092797B2 (en) | 2010-09-22 | 2015-07-28 | The Nielsen Company (Us), Llc | Methods and apparatus to analyze and adjust demographic information |
US20150271012A1 (en) * | 2008-06-06 | 2015-09-24 | Alibaba Group Holding Limited | Promulgating information on websites using servers |
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US9641336B2 (en) | 2013-12-31 | 2017-05-02 | The Nielsen Company (Us), Llc | Methods and apparatus to collect distributed user information for media impressions and search terms |
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US10068246B2 (en) | 2013-07-12 | 2018-09-04 | The Nielsen Company (Us), Llc | Methods and apparatus to collect distributed user information for media impressions |
US10147114B2 (en) | 2014-01-06 | 2018-12-04 | The Nielsen Company (Us), Llc | Methods and apparatus to correct audience measurement data |
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US10205994B2 (en) | 2015-12-17 | 2019-02-12 | The Nielsen Company (Us), Llc | Methods and apparatus to collect distributed user information for media impressions |
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Families Citing this family (1)
Publication number | Priority date | Publication date | Assignee | Title |
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Family Cites Families (2)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US7137009B1 (en) * | 2000-01-06 | 2006-11-14 | International Business Machines Corporation | Method and apparatus for securing a cookie cache in a data processing system |
CN100401696C (en) * | 2006-07-04 | 2008-07-09 | 陈玲玲 | Method for detecting number of computer users in inner compute network |
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